When a touch operation is performed with one finger, this touch operation performed with one finger is judged to be a single-point operation performed on one control point on a mesh image constituted by Bezier curves and deformation processing is performed in which the corresponding point is moved in accordance with the movement of the one touching finger. On the other hand, when a touch operation is performed with a plurality of fingers, it is judged to be a multi-point operation performed on all control points on the mesh image constituted by Bezier curves , and deformation processing is performed in which all the control points on the mesh image are moved in accordance with the movements of the plurality of fingers with the linearity of the mesh image being maintained.

The present invention discloses a multispectral stereo camera self-calibration algorithm based on track feature registration, and belongs to the field of image processing and computer vision. Optimal matching points are obtained by extracting and matching motion tracks of objects, and external parameters are corrected accordingly. Compared with an ordinary method, the present invention uses the tracks of moving objects as the features required for self-calibration. The advantage of using the tracks is good cross-modal robustness. In addition, direct matching of the tracks also saves the steps of extraction and matching the feature points, thereby achieving the advantages of simple operation and accurate results.

Scene text information extraction of desired text information from an image can be performed and managed. An information management component (IMC) can determine an anchor word based on analysis of an image. To facilitate determining desired text information in the image, WIC can re-orient the image to zero or substantially zero degrees if it determines that the orientation is skewed. IMC can utilize a neural network to determine and apply bounding boxes to text strings in the image. Using a rules-based approach or machine learning techniques, employing a trained machine learning component, IMC can utilize the anchor word along with inline grouping of textual information in the image, deep text recognition analysis, or bounding box prediction to determine or predict the desired text information in the image. IMC can facilitate presenting the desired text information, anchor word, or other information obtained from the image in an editable format.

Aspects of the disclosure can provide method for identifying a face where multiple images to be identified are received. Each of the multiple images includes a face image part. Each face image of face images in the multiple images to be identified is extracted. An initial figure identification result of identifying a figure in the each face image is determined by matching a face in the each face image respectively to a face in a target image in an image identification library. The face images are grouped. A target figure identification result for each face image in each group is determined according to the initial figure identification result for the each face image in the each group.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, in real-time from an image capture device, a video stream comprising images of a document by a computing device. The computing device provides, for display in an image preview window, the video stream overlaid with a graphical capture guide. In response to detecting a lighting artifact in at least one image of the video stream, the computing device modifies the graphical capture guide within the image preview window. The computing device captures one or more of the images of the document from the video stream.

Images of an unknown item picked from a store are processed to produce a cropped image. The cropped image is processed to produce a brightness/perspective corrected image, and the brightness/perspective corrected image is processed to produce a low-resolution final image. Image features of the low-resolution final image are extracted and compared against known item features for known items to identify an item code for a known item.

Systems and methods here may be used for pre-processing images, including using a computer for receiving a pixelated image of a paper document of an original size, downscaling the received pixelated image, employing a neural network algorithm to the downscaled image to identify four corners of the paper document in the received pixelated image, re-enlarging the downscaled image to the original size, identifying each of four corners of the paper document in the pixelated image, determining a quadrilateral composed of lines that intersect at four angles at the four corners of the paper document in the pixelated image, defining a projective plane of the pixelated image, and determining an inverse transformation of the pixelated image to transform the projective plane quadrilateral into a right angled rectangle.

An operating method of a slope estimating apparatus is provided. The operating method of the slope estimating apparatus including at least one camera includes obtaining a forward image through the at least one camera, detecting a lane included in the forward image, dividing the forward image into a plurality of smaller regions in a horizontal direction, identifying a plurality of lane segments included in each of the plurality of smaller regions, obtaining a plurality of coordinate values forming each of the plurality of lane segments, and obtaining a pitch angle of each of the plurality of smaller regions based on the obtained plurality of coordinate values.

The present disclosure describes method, apparatus, and storage medium for obtaining object information. The method includes obtaining a to-be-tracked image comprising at least one object and at least one reference image comprising a plurality of objects; extracting a to-be-tracked image block comprising a plurality of to-be-tracked points from the to-be-tracked image and extracting a reference image block comprising a plurality of reference points from a reference image of the at least one reference image; constructing a point transformation relationship between the to-be-tracked image block and the reference image block based on a position relationship between the plurality of to-be-tracked points and a position relationship between the plurality of reference points; and obtaining a position of a reference point in the reference image corresponding to a to-be-tracked point based on the point transformation relationship, to determine an object in the reference image corresponding to the at least one object.

The present invention provides a processing system (10) including: a sample image generation unit (11) that generates a plurality of sample images being each associated with a partial region of a first image generated using a first lens; an estimation unit (12) that generates an image content estimation result indicating a content for each of the sample images using an estimation model generated by machine learning using a second image generated using a second lens differing from the first lens; a task execution unit (14) that estimates a relative positional relationship of a plurality of the sample images in the first image; a determination unit (15) that determines whether an estimation result of the relative positional relationship is correct; and a correction unit (16) that corrects a value of a parameter of the estimation model when the estimation result of the relative positional relationship is determined to be incorrect.